查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Nanni ng, People's Republic of China, by NewsRx editors, the research stated, "The fun damental objective of this paper is to use Machine Learning (ML) methods for bui lding models on temperature (T) prediction using input features r and z for a me mbrane separation process. A hybrid model was developed based on computational f luid dynamics (CFD) to simulate the separation process and integrate the results into machine learning models." Our news editors obtained a quote from the research from the Guangxi University of Finance and Economics, "The CFD simulations were performed to estimate temper ature distribution in a vacuum membrane distillation (VMD) process for separatio n of liquid mixtures. The evaluated ML models include Support Vector Machine (SV M), Elastic Net Regression (ENR), Extremely Randomized Trees (ERT), and Bayesian Ridge Regression (BRR). Performance was improved using Differential Evolution ( DE) for hyper-parameter tuning, and model validation was performed using Monte C arlo Cross-Validation. The results clearly indicated the models' effectiveness i n temperature prediction, with SVM outperforming other models in terms of accura cy. The SVM model had a mean R value of 0.9969 and a standard deviation of 0.000 1, indicating a strong and consistent fit to the membrane data. Furthermore, it exhibited the lowest mean squared error, mean absolute error, and mean absolute percentage error, signifying superior predictive accuracy and reliability. These outcomes highlight the importance of selecting a suitable model and optimizing hyperparameters to guarantee accurate predictions in ML tasks."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Liver Cance r is the subject of a report. According to news originating from Zhejiang, Peopl e's Republic of China, by NewsRx correspondents, research stated, "The highly he terogeneity of the tumor microenvironment (TME) in hepatocellular carcinoma (HCC ) results in diverse clinical outcomes and therapeutic responses. This study aim ed to investigate potential intercellular crosstalk and its impact on clinical o utcomes and therapeutic responses." Our news journalists obtained a quote from the research from the Zhejiang Univer sity School of Medicine, "Single-cell RNA sequencing (scRNA-seq), spatial transc riptomics (ST) and bulk RNA sequencing (RNA-seq) datasets were integrated to com prehensively analyze the intercellular interactions within the TME. Multiplex im munohistochemistry was conducted to validate the intercellular interactions. A m achine learning-based integrative procedure was used in bulk RNA-seq datasets to generate a risk model to predict prognosis and therapeutic responses. Survival analyses based on the bulk RNA-seq datasets revealed the negative impact of the naive Cluster of Differentiation 4 (CD4) T cells and Secreted Phosphoprotein 1 ( SPP1) macrophages on prognosis. Furthermore, their intricate intercellular cross talk and spatial colocalization were also observed by scRNA-seq and ST analyses. Based on this crosstalk, a machine learning model, termed the naive CD4 T cell and SPP1 macrophage prognostic score (TMPS), was established in the bulk-RNA seq datasets for prognostic prediction. The TMPS achieved C-index values of 0.785, 0.715, 0.692 and 0.857, respectively, across 4 independent cohorts. A low TMPS w as associated with a significantly increased survival rates, improved response t o immunotherapy and reduced infiltration of immunosuppressive cells, such as. re gulatory T cells. Finally, 8 potential sensitive drugs and 6 potential targets w ere predicted for patients based on their TMPS. The crosstalk between naive CD4 T cells and SPP1 macrophages play a crucial role in the TME."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ro botics. According to news originating from Bloomington, Indiana, by NewsRx edito rs, the research stated, "This study examined the effects of embodied learning e xperiences on students' understanding of computational thinking (CT) concepts an d their ability to solve CT problems." Financial supporters for this research include National Science Foundation. Our news reporters obtained a quote from the research from Indiana University: " In a mixed-reality learning environment, students mapped CT concepts, such as se quencing and loops, onto their bodily movements. These movements were later appl ied to robot programming tasks, where students used the same CT concepts in a di fferent modality. By explicitly connecting embodied actions with programming tas ks, the intervention aimed to enhance students' comprehension and transfer of CT skills. Forty-four first- and second-grade students participated in the study. The results showed significant improvements in students' CT competency and posit ive attitudes toward CT."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on artificial intelligence have been published. According to news originating from Jahangirnagar University by NewsRx correspondents, research stated, "The birth weight of a newborn is a crucial factor that affects their overall health and future well-being. Low birt h weight (LBW) is a widespread global issue, which the World Health Organization defines as weighing less than 2,500 g. LBW can have severe negative consequence s on an individual's health, including neonatal mortality and various health con cerns throughout their life."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on robotics have been published. According to news reporting from Lexington, Kentucky, by NewsRx journalists, research stated, "This paper presents the results of an experiment that was designed to explore whether users assigned an ethnic identity to the M isty II robot based on the robot's voice accent, place of origin, and given name ." Financial supporters for this research include University of Tennessee-knoxville ; University of Kentucky; Sec Emerging Scholars Award. Our news editors obtained a quote from the research from University of Kentucky: "To explore this topic a 2 x 3 within subject study was run which consisted of a humanoid robot speaking with a male or female gendered voice and using three d ifferent voice accents (Chinese, American, Mexican). Using participants who iden tified as American, the results indicated that users were able to identify the g ender and ethnic identity of the Misty II robot with a high degree of accuracy b ased on a minimum set of social cues. However, the version of Misty II presentin g with an American ethnicity was more accurately identified than a robot present ing with cues signaling a Mexican or Chinese ethnicity."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting originating from Liverpool, United Kingdom, by NewsRx correspondents, research stated, "Endowing robots with the ability to maintain precise interaction force is critical for performing force control task s in dynamic environments characterized by unknown and varying stiffness and geo metry, such as aircraft wing skins and other thin, soft materials. This article presents an adaptive force-tracking admittance controller (AFTAC), ensuring trac king performance through the meticulous design of both the force-based outer loo p and the position-based inner loop." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Key Research & Development Program of China, Fundamental Research Funds for the Central Universities, Chongqing Top-N otch Young Talents Program, China Scholarship Council.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting originating in Copenhagen, Denmark, by NewsRx editors, the research stated, "This article discusses two seemingly u nrelated but homologous challenges to established sociological thinking, namely machine learning technologies and postcolonial critique. Both of these confront conventional human-centric sociological notions." The news reporters obtained a quote from the research from the University of Cop enhagen, "Where the rise of machine learning should prompt sociologists to take the agency of nonhuman systems seriously, postcolonial critique challenges the i dea of Eurocentric human agency. I discuss whether this dual agency challenge ca n be addressed through Latour's actor-network theory and Luhmann's sociological systems theory - both of which explicitly aim to transcend classical human-centr ic approaches. I argue that Latour's work can align with postcolonial sociology. However, despite broadening the notion of agency, his actor-network concept rem ains strongly human-centric. It merely expands the range of actors with which hu mans engage rather than analysing interactions among nonhuman actants, such as m achine learning systems."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of London, United Kingdom , by NewsRx editors, research stated, "Solid-state sodium batteries require effe ctive electrolytes that conduct at room temperature. The NaPnCh (Pn = P, Sb; Ch = S, Se) family has been studied for their high Na ion conductivity." Our news journalists obtained a quote from the research from Imperial College Lo ndon, "The population of Na vacancies, which mediate ion diffusion in these mate rials, can be enhanced through aliovalent doping on the pnictogen site. To probe the microscopic role of extrinsic doping and its impact on diffusion and phase stability, we trained a machine learning force field for Na W Sb S based on an e quivariant graph neural network. Analysis of large-scale molecular dynamics traj ectories shows that an increased Na vacancy population stabilizes the global cub ic phase at lower temperatures with enhanced Na ion diffusion and that the expli cit role of the substitutional W dopants is limited. In the global cubic phase, we observe large and long-lived deviations of atoms from the averaged symmetry, echoing recent experimental suggestions."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Huangshi, P eople's Republic of China, by NewsRx editors, research stated, "Spectral and tex ture features play important roles in plantation leaf area index (LAI) estimatio n, and their combination may enhance LAI inversion accuracy. Furthermore, resear ch on the impact of different machine learning (ML) models on their hyperparamet er combinations and splitting ratios remains challenging." Our news reporters obtained a quote from the research from Hubei Normal Universi ty: "In our study, experiments based on spectral and textural features of GF-6 W FV data were conducted on Eucalyptus grandis plantation forests in Huangmian Tow n, Guangxi, China. ML methods such as multiple stepwise regression (MSR), random forest (RF), back-propagation neural network (BPNN), and support vector regress ion (SVR) were mainly utilized to perform model hyper-parameter tuning and split -ratio analysis in order to estimate the LAI. The results of the study showed th at spectral and gray level co-occurrence matrix (GLCM) texture features were ver y sensitive to changes in Eucalyptus grandis LAI. The accuracy of combining the two was 10% higher than when they were not combined. Furthermore, it was found that the nonlinear methods (RF, BPNN, and SVR) outperformed the lin ear method (MSR), with the average Rmax2 of the nonlinear model being 26% higher than that of the linear model, and the RMSE value being 29% lower than that of the linear model. In addition, by analyzing different combina tions of features, model hyperparameter fine-tuning, and splitting ratios in the nonlinear model, it was found that the splitting ratios of different combinatio ns of model hyperparameters have a great impact on the accuracy of the model. A total of 12 out of 21 data sets showed high accuracy and stability at a split ra tio of 8.5:1.5 (ratio of 0.85), with the best-performing RF model differing from the lowest by 91% for Rmax2 and 39% for Rstd2."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics have been published. According to news reporting originating in Los Angeles, Califor nia, by NewsRx journalists, research stated, "Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return-to-sport rates. Unfortunately, the mechanics of ligament injury are diff icult to study in vivo, and computational studies provide limited insight." Financial support for this research came from National Science Foundation (NSF).
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